Data Engineer at Digible
Digible, Inc. is an emerging startup in the digital marketing and technology field. We bring the industry's most advanced digital strategies, products and research to scale. Our focus is multifamily marketing and student housing with a client base spanning across 50 markets. Digible has big plans for expansion in 2020 for both our agency and SAAS platform. We are energetically pursuing top talent in the Denver area to grow our team and help craft the company’s future.
Digible, Inc. is looking for an experienced Data Engineer to access 3rd party API’s, build data pipelines, develop/maintain ELT process, and develop BI Data Marts. In partnership with our Data Ops Engineer and Data Scientist, the Data Engineer will also be part of our roadmap to scale and productionize machine learning algorithms. This role will play an integral part in Digible’s product & services roadmap, and will be part of our DNA team reporting to the Chief Data Officer.
- API development & maintenance for data retrieval from various 3rd party data sources including Ad Tech, CRM’s, etc.
- Develop and maintain data pipelines to move data from source/data lake/data warehouse/OLTP
- Conduct appropriate transformations on the data to meet requirements for BI and the Fiona app.
- BI Development including but not limited to DataMart – star schema, metric development, embedded analytics, and data visualization
- Data architecture, data models, and database management
- Bachelor Degree in Data Science, Computer Science, Engineering or related discipline or equivalent business experience in data architecture, data engineering, BI development, and database management
- A Master’s Degree is preferred
- 2+ years’ experience in a Data Engineering role developing and managing API’s and data pipelines
- Advanced SQL experience and database design with an emphasis on BI
- 3+ years of Python programming and development
- Work experience in an AdTech or Martech company is preferred
- Some experience with big data engineering including distributed cluster computing for scaling machine and deep learning
Knowledge and Skills:
- Capable of working with large data sets from design to execution
- Able to demonstrate advanced computer and analytical skills with particular knowledge and understanding of the following storage, computing and machine learning tools:
- PostgreSQL and MS SQL Server
- S3 and Snowflake or equivalent cloud-based data lake/warehouse environment
- Amazon Glue, BCP utility, Pentaho, etc.
- Apache Spark, Databricks, Data Flow
- Redis or other in memory caching solutions
- Strong knowledge and working experience with Software Engineering development and deployment practices, Docker, Flask, gunicorn, App Engine, and Kubernetes
- Demonstrate compatibility with TDD and Twelve Factor app methodologies
- Proficient with GitHub workflows and AWS services (i.e. Lambda, SNS, SQS, ECR, ECS, EKS, CloudWatch, EC2, Sagemaker, CloudFormation, Step Functions, and Secrets Manager)
- Sprint, Scrum, and/or Kanban experience with comfort level to work in iterative fast cycles
- Understanding of data mining, machine learning, and statistical models including regression, PCA, decision trees, time series, and neural networks. Libraries such as Pytorch, Scikit, and/or Tensorflow, Keras
- Experience and understanding of web data including ad server logs, click stream, cookie pools, device fingerprinting, UID’s, UTM, Floodlight, and Google Analytics
- Modest experience with BI tools such as Periscope, Scisense, Tableau, Looker, etc.
- Strong curiosity and desire to design build and automate
- Focuses on accuracy with a meticulous attention to detail
- Ability to work well independently in a fast-paced environment
- Ability to work in and with teams across the whole organization
- Comfortable in startup environment including wearing various hats
- Ability to multi task, prioritize and get things done
- An aptitude for seeing the big picture and possessing an entrepreneurial spirit
- Loves working with data!
- Competitive salary
- Full benefits
- 401k match
- Flexible work schedule with the ability to work remote 3 days week. Temporarily 100% due to Covid-19
- And many other perks